Massively Multilingual Neural Machine Translation
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Roee Aharoni, Melvin Johnson, Orhan Firat. Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). 2019.
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Multilingual modeling has not been systematically explored for code translation.
“Multilingual modeling shows great potential in neural machine translation (Aharoni et al., 2019;Wang et al., 2020;Zhu et al., 2023), but it has not been systematically explored for code translation.”
From CodeTransOcean: A Comprehensive Multilingual Benchmark for Code Translation (2023) · cites this paper as Aharoni et al., 2019
Multilingual modeling has been pivotal in broadening the applicability of neural machine translation, primarily evidenced in enhancing performance of low-resource languages and cross-language transfer learning.
“Multilingual modeling has been pivotal in broadening the applicability of neural machine translation (Aharoni et al., 2019;Wang et al., 2020;Zhu et al., 2023;Johnson et al., 2017).This is primarily evidenced in enhancing the performance of low-resource languages and cross-language transfer learning (Mohammadshahi et al., 2022;Zoph et al., 2016;Nguyen and Chiang, 2017;Johnson et al., 2017).”
From CodeTransOcean: A Comprehensive Multilingual Benchmark for Code Translation (2023) · cites this paper as Aharoni et al., 2019
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“duce the performance degradation when increasing the number of languages, or using such models for multilingual transfer learning (McCann et al., 2017; Eriguchi et al., 2018; Artetxe and Schwenk, 2018).”
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- Authors
- Aharoni, R., Johnson, M., & Firat, O.
- Affiliations
- Google (United States) (US)
- Venue
- Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)
- Published
- 2019
- Pages
- 3874-3884
- OpenAlex
- W2919290281
- Cited by
- 402
- References
- 2
- Citations by year
- 2026: 17 · 2025: 25 · 2024: 26 · 2023: 81 · 2022: 60 · 2021: 97 · 2020: 72 · 2019: 24
- FWCI
- 24.20
- Type
- conference paper
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by
- Locations
- Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) (publishedVersion, cc-by)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Natural Language Processing Techniques
- Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
- Physical Sciences › Computer Science › Artificial Intelligence › Speech Recognition and Synthesis
- Keywords
- neural machine translation, multilingual machine translation, low-resource languages, low-resource language pairs
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